Research Associate

4 weeks ago


Leicester, Leicester, United Kingdom University Of Leicester Full time
About the Role

The University of Leicester Ulverscroft Eye Unit is seeking a highly skilled Postdoctoral Research Associate to join our team. As a key member of our research group, you will be responsible for developing and implementing an independent research program in line with our strategic priorities.

Our team is dedicated to exploring the potential of retinal image-derived phenotypes in disease prediction and modeling. We are looking for a candidate with a strong background in bioinformatics, computational biology, or a closely related field. Experience with genetic data analysis and statistical genetics methodologies is essential.

Key Responsibilities
  • Develop and implement an independent research program in line with our strategic priorities
  • Manage large-scale genotype and phenotype datasets
  • Supervise clinical studies and support research staff and PhD/iMSc/project students
  • Contribute to the development of new research projects and collaborations
What We Offer

As a member of our team, you will have access to state-of-the-art computational and experimental resources. You will have the opportunity to work on multidisciplinary projects, aiming to bridge the gap between computational analysis and experimental biology.

Our team benefits from world-leading data science infrastructure and a dedicated research computing support service. We also have a strong track record in career development for early-career researchers, with many of our team members having secured competitive external fellowships.

About You

We are looking for a creative and ambitious individual with excellent communication skills and a keen interest in tackling challenging projects. You should have a strong background in bioinformatics, computational biology, or a closely related field, and experience with genetic data analysis and statistical genetics methodologies.

Proficiency in statistical programming languages (e.g., R, Python) and a good understanding of genetic and molecular biology concepts are also required. Knowledge in CRISPR-Cas9 technology and familiarity with artificial intelligence and machine learning techniques applied to biological datasets would be beneficial.


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